Raw Data Summary

Dataset statistics

Number of variables	45
Number of observations	240000
Missing cells	8890408
Missing cells (%)	82.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	84.2 MiB
Average record size in memory	368.0 B

Variable types

Categorical	25
Numeric	12
Unsupported	8

Warnings

`placement_support_banner_tab_clicked` has constant value "1.0"	Constant
`programme_curriculum` has constant value "1.0"	Constant
`programme_faculty` has constant value "1.0"	Constant
`request_callback_on_instant_customer_support_cta_clicked` has constant value "1.0"	Constant
`created_date` has a high cardinality: 234753 distinct values	High cardinality
`city_mapped` has a high cardinality: 4597 distinct values	High cardinality
`first_utm_source_c` has a high cardinality: 142 distinct values	High cardinality
`total_leads_droppped` is highly correlated with `call_us_button_clicked` and 6 other fields	High correlation
`call_us_button_clicked` is highly correlated with `total_leads_droppped` and 4 other fields	High correlation
`career_assistance` is highly correlated with `careers` and 4 other fields	High correlation
`career_impact` is highly correlated with `careers` and 8 other fields	High correlation
`careers` is highly correlated with `career_assistance` and 5 other fields	High correlation
`companies` is highly correlated with `total_leads_droppped` and 12 other fields	High correlation
`download_button_clicked` is highly correlated with `total_leads_droppped` and 8 other fields	High correlation
`emi_partner_click` is highly correlated with `total_leads_droppped` and 12 other fields	High correlation
`emi_plans_clicked` is highly correlated with `total_leads_droppped` and 12 other fields	High correlation
`fee_component_click` is highly correlated with `download_button_clicked` and 3 other fields	High correlation
`hiring_partners` is highly correlated with `total_leads_droppped` and 3 other fields	High correlation
`live_chat_button_clicked` is highly correlated with `careers` and 1 other fields	High correlation
`placement_support` is highly correlated with `emi_partner_click` and 2 other fields	High correlation
`shorts_entry_click` is highly correlated with `emi_partner_click`	High correlation
`social_referral_click` is highly correlated with `whatsapp_chat_click`	High correlation
`specialisation_tab_clicked` is highly correlated with `companies` and 2 other fields	High correlation
`specializations` is highly correlated with `download_button_clicked` and 2 other fields	High correlation
`specilization_click` is highly correlated with `download_button_clicked` and 4 other fields	High correlation
`syllabus` is highly correlated with `career_impact` and 3 other fields	High correlation
`syllabus_expand` is highly correlated with `call_us_button_clicked` and 11 other fields	High correlation
`syllabus_submodule_expand` is highly correlated with `companies` and 8 other fields	High correlation
`tab_career_assistance` is highly correlated with `career_impact` and 7 other fields	High correlation
`tab_job_opportunities` is highly correlated with `career_impact` and 6 other fields	High correlation
`tab_student_support` is highly correlated with `career_assistance` and 4 other fields	High correlation
`view_programs_page` is highly correlated with `emi_plans_clicked`	High correlation
`whatsapp_chat_click` is highly correlated with `total_leads_droppped` and 9 other fields	High correlation
`app_complete_flag` is highly correlated with `call_us_button_clicked` and 3 other fields	High correlation
`total_leads_droppped` is highly correlated with `call_us_button_clicked` and 6 other fields	High correlation
`referred_lead` is highly correlated with `social_referral_click` and 1 other fields	High correlation
`call_us_button_clicked` is highly correlated with `total_leads_droppped` and 4 other fields	High correlation
`career_assistance` is highly correlated with `careers` and 5 other fields	High correlation
`career_impact` is highly correlated with `careers` and 8 other fields	High correlation
`careers` is highly correlated with `career_assistance` and 3 other fields	High correlation
`companies` is highly correlated with `total_leads_droppped` and 12 other fields	High correlation
`download_button_clicked` is highly correlated with `total_leads_droppped` and 10 other fields	High correlation
`emi_partner_click` is highly correlated with `total_leads_droppped` and 16 other fields	High correlation
`emi_plans_clicked` is highly correlated with `total_leads_droppped` and 12 other fields	High correlation
`fee_component_click` is highly correlated with `download_button_clicked` and 4 other fields	High correlation
`hiring_partners` is highly correlated with `career_assistance` and 3 other fields	High correlation
`live_chat_button_clicked` is highly correlated with `careers` and 3 other fields	High correlation
`placement_support` is highly correlated with `emi_partner_click` and 2 other fields	High correlation
`shorts_entry_click` is highly correlated with `emi_partner_click` and 1 other fields	High correlation
`social_referral_click` is highly correlated with `referred_lead` and 1 other fields	High correlation
`specialisation_tab_clicked` is highly correlated with `companies` and 8 other fields	High correlation
`specializations` is highly correlated with `download_button_clicked` and 6 other fields	High correlation
`specilization_click` is highly correlated with `total_leads_droppped` and 5 other fields	High correlation
`syllabus` is highly correlated with `career_assistance` and 4 other fields	High correlation
`syllabus_expand` is highly correlated with `total_leads_droppped` and 14 other fields	High correlation
`syllabus_submodule_expand` is highly correlated with `companies` and 9 other fields	High correlation
`tab_career_assistance` is highly correlated with `career_assistance` and 8 other fields	High correlation
`tab_job_opportunities` is highly correlated with `career_impact` and 6 other fields	High correlation
`tab_student_support` is highly correlated with `career_assistance` and 2 other fields	High correlation
`view_programs_page` is highly correlated with `emi_partner_click` and 1 other fields	High correlation
`whatsapp_chat_click` is highly correlated with `download_button_clicked` and 9 other fields	High correlation
`app_complete_flag` is highly correlated with `call_us_button_clicked` and 3 other fields	High correlation
`total_leads_droppped` is highly correlated with `call_us_button_clicked` and 3 other fields	High correlation
`referred_lead` is highly correlated with `social_referral_click`	High correlation
`call_us_button_clicked` is highly correlated with `total_leads_droppped` and 4 other fields	High correlation
`career_assistance` is highly correlated with `careers` and 4 other fields	High correlation
`career_impact` is highly correlated with `careers` and 8 other fields	High correlation
`careers` is highly correlated with `career_assistance` and 3 other fields	High correlation
`companies` is highly correlated with `total_leads_droppped` and 12 other fields	High correlation
`download_button_clicked` is highly correlated with `call_us_button_clicked` and 5 other fields	High correlation
`emi_partner_click` is highly correlated with `total_leads_droppped` and 9 other fields	High correlation
`emi_plans_clicked` is highly correlated with `total_leads_droppped` and 6 other fields	High correlation
`fee_component_click` is highly correlated with `syllabus_submodule_expand`	High correlation
`hiring_partners` is highly correlated with `career_assistance` and 2 other fields	High correlation
`live_chat_button_clicked` is highly correlated with `careers` and 1 other fields	High correlation
`placement_support` is highly correlated with `emi_partner_click` and 1 other fields	High correlation
`shorts_entry_click` is highly correlated with `whatsapp_chat_click`	High correlation
`social_referral_click` is highly correlated with `referred_lead` and 1 other fields	High correlation
`specialisation_tab_clicked` is highly correlated with `companies` and 5 other fields	High correlation
`specializations` is highly correlated with `download_button_clicked` and 3 other fields	High correlation
`specilization_click` is highly correlated with `download_button_clicked` and 3 other fields	High correlation
`syllabus` is highly correlated with `career_assistance` and 3 other fields	High correlation
`syllabus_expand` is highly correlated with `call_us_button_clicked` and 9 other fields	High correlation
`syllabus_submodule_expand` is highly correlated with `companies` and 4 other fields	High correlation
`tab_career_assistance` is highly correlated with `career_impact` and 4 other fields	High correlation
`tab_job_opportunities` is highly correlated with `career_impact` and 3 other fields	High correlation
`tab_student_support` is highly correlated with `career_assistance` and 1 other fields	High correlation
`view_programs_page` is highly correlated with `emi_partner_click` and 1 other fields	High correlation
`whatsapp_chat_click` is highly correlated with `emi_partner_click` and 7 other fields	High correlation
`app_complete_flag` is highly correlated with `call_us_button_clicked` and 2 other fields	High correlation
`tab_job_opportunities` is highly correlated with `emi_partner_click` and 10 other fields	High correlation
`placement_support` is highly correlated with `first_utm_medium_c`	High correlation
`first_utm_medium_c` is highly correlated with `placement_support` and 8 other fields	High correlation
`emi_partner_click` is highly correlated with `tab_job_opportunities` and 15 other fields	High correlation
`careers` is highly correlated with `tab_job_opportunities` and 8 other fields	High correlation
`emi_plans_clicked` is highly correlated with `tab_job_opportunities` and 13 other fields	High correlation
`app_complete_flag` is highly correlated with `first_platform_c` and 1 other fields	High correlation
`specialisation_tab_clicked` is highly correlated with `emi_partner_click` and 9 other fields	High correlation
`syllabus_expand` is highly correlated with `tab_job_opportunities` and 13 other fields	High correlation
`syllabus_submodule_expand` is highly correlated with `tab_job_opportunities` and 13 other fields	High correlation
`specializations` is highly correlated with `first_utm_medium_c` and 6 other fields	High correlation
`tab_student_support` is highly correlated with `tab_job_opportunities` and 9 other fields	High correlation
`tab_career_assistance` is highly correlated with `tab_job_opportunities` and 8 other fields	High correlation
`hiring_partners` is highly correlated with `tab_job_opportunities` and 5 other fields	High correlation
`live_chat_button_clicked` is highly correlated with `syllabus_submodule_expand` and 2 other fields	High correlation
`first_platform_c` is highly correlated with `tab_job_opportunities` and 9 other fields	High correlation
`career_impact` is highly correlated with `tab_job_opportunities` and 7 other fields	High correlation
`syllabus` is highly correlated with `emi_partner_click` and 7 other fields	High correlation
`whatsapp_chat_click` is highly correlated with `first_utm_medium_c` and 8 other fields	High correlation
`total_leads_droppped` is highly correlated with `emi_partner_click` and 12 other fields	High correlation
`download_button_clicked` is highly correlated with `emi_plans_clicked` and 10 other fields	High correlation
`career_assistance` is highly correlated with `tab_job_opportunities` and 13 other fields	High correlation
`specilization_click` is highly correlated with `first_utm_medium_c` and 2 other fields	High correlation
`fee_component_click` is highly correlated with `first_utm_medium_c` and 6 other fields	High correlation
`city_mapped` has 9403 (3.9%) missing values	Missing
`1_on_1_industry_mentorship` has 240000 (100.0%) missing values	Missing
`call_us_button_clicked` has 239998 (> 99.9%) missing values	Missing
`career_assistance` has 239996 (> 99.9%) missing values	Missing
`career_coach` has 240000 (100.0%) missing values	Missing
`career_impact` has 239995 (> 99.9%) missing values	Missing
`careers` has 239980 (> 99.9%) missing values	Missing
`chat_clicked` has 240000 (100.0%) missing values	Missing
`companies` has 239998 (> 99.9%) missing values	Missing
`download_button_clicked` has 239893 (> 99.9%) missing values	Missing
`download_syllabus` has 240000 (100.0%) missing values	Missing
`emi_partner_click` has 239921 (> 99.9%) missing values	Missing
`emi_plans_clicked` has 239939 (> 99.9%) missing values	Missing
`fee_component_click` has 239995 (> 99.9%) missing values	Missing
`hiring_partners` has 239991 (> 99.9%) missing values	Missing
`homepage_upgrad_support_number_clicked` has 240000 (100.0%) missing values	Missing
`industry_projects_case_studies` has 240000 (100.0%) missing values	Missing
`live_chat_button_clicked` has 239982 (> 99.9%) missing values	Missing
`payment_amount_toggle_mover` has 240000 (100.0%) missing values	Missing
`placement_support` has 239997 (> 99.9%) missing values	Missing
`placement_support_banner_tab_clicked` has 239999 (> 99.9%) missing values	Missing
`program_structure` has 240000 (100.0%) missing values	Missing
`programme_curriculum` has 239999 (> 99.9%) missing values	Missing
`programme_faculty` has 239999 (> 99.9%) missing values	Missing
`request_callback_on_instant_customer_support_cta_clicked` has 239998 (> 99.9%) missing values	Missing
`shorts_entry_click` has 239987 (> 99.9%) missing values	Missing
`social_referral_click` has 239995 (> 99.9%) missing values	Missing
`specialisation_tab_clicked` has 239956 (> 99.9%) missing values	Missing
`specializations` has 239996 (> 99.9%) missing values	Missing
`specilization_click` has 239993 (> 99.9%) missing values	Missing
`syllabus` has 239971 (> 99.9%) missing values	Missing
`syllabus_expand` has 239906 (> 99.9%) missing values	Missing
`syllabus_submodule_expand` has 239958 (> 99.9%) missing values	Missing
`tab_career_assistance` has 239975 (> 99.9%) missing values	Missing
`tab_job_opportunities` has 239981 (> 99.9%) missing values	Missing
`tab_student_support` has 239992 (> 99.9%) missing values	Missing
`view_programs_page` has 239988 (> 99.9%) missing values	Missing
`whatsapp_chat_click` has 239975 (> 99.9%) missing values	Missing
`created_date` is uniformly distributed	Uniform
`call_us_button_clicked` is uniformly distributed	Uniform
`companies` is uniformly distributed	Uniform
`app_complete_flag` is uniformly distributed	Uniform
`1_on_1_industry_mentorship` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`career_coach` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`chat_clicked` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`download_syllabus` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`homepage_upgrad_support_number_clicked` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`industry_projects_case_studies` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`payment_amount_toggle_mover` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`program_structure` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2023-01-18 13:24:24.931567
Analysis finished	2023-01-18 13:25:24.921443
Duration	59.99 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

created_date
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	234753
Distinct (%)	97.8%
Missing	0
Missing (%)	0.0%
Memory size	3.7 MiB

2021-12-14 04:55:05	10
2021-12-16 19:28:19	5
2021-12-06 06:48:43	5
2022-02-03 12:42:15	4
2021-08-08 14:28:39	4
Other values (234748)	239972

Length

Max length	19
Median length	19
Mean length	19
Min length	19

Characters and Unicode

Total characters	4560000
Distinct characters	13
Distinct categories	4 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	229720 ?
Unique (%)	95.7%

Sample

1st row	2021-08-13 10:44:09
2nd row	2021-11-04 06:34:10
3rd row	2021-07-29 14:01:00
4th row	2021-12-01 13:21:54
5th row	2021-12-10 07:22:51

Common Values

Value	Count	Frequency (%)
2021-12-14 04:55:05	10	< 0.1%
2021-12-16 19:28:19	5	< 0.1%
2021-12-06 06:48:43	5	< 0.1%
2022-02-03 12:42:15	4	< 0.1%
2021-08-08 14:28:39	4	< 0.1%
2022-01-20 08:46:25	4	< 0.1%
2022-01-05 09:34:36	4	< 0.1%
2021-08-08 15:51:55	4	< 0.1%
2022-01-17 10:31:44	4	< 0.1%
2021-12-29 16:31:01	4	< 0.1%
Other values (234743)	239952	> 99.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2021-08-10	1725	0.4%
2021-09-13	1581	0.3%
2021-11-16	1525	0.3%
2022-01-20	1520	0.3%
2022-01-03	1517	0.3%
2021-12-01	1507	0.3%
2021-11-29	1486	0.3%
2021-12-29	1484	0.3%
2022-01-04	1456	0.3%
2021-11-17	1449	0.3%
Other values (69354)	464750	96.8%

Most occurring characters

Value	Count	Frequency (%)
2	825421	18.1%
1	752578	16.5%
0	741639	16.3%
-	480000	10.5%
:	480000	10.5%
	240000	5.3%
3	186539	4.1%
5	184878	4.1%
4	179779	3.9%
8	129638	2.8%
Other values (3)	359528	7.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3360000	73.7%
Dash Punctuation	480000	10.5%
Other Punctuation	480000	10.5%
Space Separator	240000	5.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	825421	24.6%
1	752578	22.4%
0	741639	22.1%
3	186539	5.6%
5	184878	5.5%
4	179779	5.4%
8	129638	3.9%
7	129041	3.8%
9	122945	3.7%
6	107542	3.2%

Dash Punctuation

Value	Count	Frequency (%)
-	480000	100.0%

Space Separator

Value	Count	Frequency (%)
	240000	100.0%

Other Punctuation

Value	Count	Frequency (%)
:	480000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	4560000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	825421	18.1%
1	752578	16.5%
0	741639	16.3%
-	480000	10.5%
:	480000	10.5%
	240000	5.3%
3	186539	4.1%
5	184878	4.1%
4	179779	3.9%
8	129638	2.8%
Other values (3)	359528	7.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4560000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	825421	18.1%
1	752578	16.5%
0	741639	16.3%
-	480000	10.5%
:	480000	10.5%
	240000	5.3%
3	186539	4.1%
5	184878	4.1%
4	179779	3.9%
8	129638	2.8%
Other values (3)	359528	7.9%

city_mapped
Categorical

HIGH CARDINALITY
MISSING

Distinct	4597
Distinct (%)	2.0%
Missing	9403
Missing (%)	3.9%
Memory size	3.7 MiB

ncr	35263
mumbai	22186
bengaluru	19530
hyderabad	14376
pune	14014
Other values (4592)	125228

Length

Max length	61
Median length	7
Mean length	6.734281018
Min length	1

Characters and Unicode

Total characters	1552905
Distinct characters	27
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2427 ?
Unique (%)	1.1%

Sample

1st row	mumbai
2nd row	ncr
3rd row	meerut
4th row	ncr
5th row	ahmedabad

Common Values

Value	Count	Frequency (%)
ncr	35263	14.7%
mumbai	22186	9.2%
bengaluru	19530	8.1%
hyderabad	14376	6.0%
pune	14014	5.8%
chennai	9697	4.0%
kolkata	8340	3.5%
lucknow	7073	2.9%
ahmedabad	6101	2.5%
jaipur	4417	1.8%
Other values (4587)	89600	37.3%
(Missing)	9403	3.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ncr	35265	15.0%
mumbai	22193	9.4%
bengaluru	19531	8.3%
hyderabad	14376	6.1%
pune	14021	6.0%
chennai	10121	4.3%
kolkata	8349	3.6%
lucknow	7073	3.0%
ahmedabad	6101	2.6%
jaipur	4645	2.0%
Other values (4688)	93479	39.8%

Most occurring characters

Value	Count	Frequency (%)
a	260306	16.8%
n	143332	9.2%
r	140618	9.1%
u	127886	8.2%
e	89195	5.7%
b	83535	5.4%
i	81499	5.2%
d	73791	4.8%
m	72086	4.6%
h	71745	4.6%
Other values (17)	408912	26.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1548348	99.7%
Space Separator	4557	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	260306	16.8%
n	143332	9.3%
r	140618	9.1%
u	127886	8.3%
e	89195	5.8%
b	83535	5.4%
i	81499	5.3%
d	73791	4.8%
m	72086	4.7%
h	71745	4.6%
Other values (16)	404355	26.1%

Space Separator

Value	Count	Frequency (%)
	4557	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1548348	99.7%
Common	4557	0.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	260306	16.8%
n	143332	9.3%
r	140618	9.1%
u	127886	8.3%
e	89195	5.8%
b	83535	5.4%
i	81499	5.3%
d	73791	4.8%
m	72086	4.7%
h	71745	4.6%
Other values (16)	404355	26.1%

Common

Value	Count	Frequency (%)
	4557	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1552905	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	260306	16.8%
n	143332	9.2%
r	140618	9.1%
u	127886	8.2%
e	89195	5.7%
b	83535	5.4%
i	81499	5.2%
d	73791	4.8%
m	72086	4.6%
h	71745	4.6%
Other values (17)	408912	26.3%

first_platform_c
Categorical

HIGH CORRELATION

Distinct	49
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.7 MiB

Level0	84532
Level3	41028
Level7	38267
Level1	20832
Level2	13284
Other values (44)	42057

Length

Max length	7
Median length	6
Mean length	6.063625
Min length	6

Characters and Unicode

Total characters	1455270
Distinct characters	14
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	8 ?
Unique (%)	< 0.1%

Sample

1st row	Level0
2nd row	Level1
3rd row	Level0
4th row	Level1
5th row	Level2

Common Values

Value	Count	Frequency (%)
Level0	84532	35.2%
Level3	41028	17.1%
Level7	38267	15.9%
Level1	20832	8.7%
Level2	13284	5.5%
Level8	10838	4.5%
Level5	9768	4.1%
Level4	5514	2.3%
Level16	3790	1.6%
Level10	3288	1.4%
Other values (39)	8859	3.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
level0	84532	35.2%
level3	41028	17.1%
level7	38267	15.9%
level1	20832	8.7%
level2	13284	5.5%
level8	10838	4.5%
level5	9768	4.1%
level4	5514	2.3%
level16	3790	1.6%
level10	3288	1.4%
Other values (39)	8859	3.7%

Most occurring characters

Value	Count	Frequency (%)
e	480000	33.0%
L	240000	16.5%
v	240000	16.5%
l	240000	16.5%
0	87917	6.0%
3	41784	2.9%
7	38362	2.6%
1	36380	2.5%
2	16844	1.2%
8	12972	0.9%
Other values (4)	21011	1.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	960000	66.0%
Decimal Number	255270	17.5%
Uppercase Letter	240000	16.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	87917	34.4%
3	41784	16.4%
7	38362	15.0%
1	36380	14.3%
2	16844	6.6%
8	12972	5.1%
5	9891	3.9%
4	6309	2.5%
6	4526	1.8%
9	285	0.1%

Lowercase Letter

Value	Count	Frequency (%)
e	480000	50.0%
v	240000	25.0%
l	240000	25.0%

Uppercase Letter

Value	Count	Frequency (%)
L	240000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1200000	82.5%
Common	255270	17.5%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	87917	34.4%
3	41784	16.4%
7	38362	15.0%
1	36380	14.3%
2	16844	6.6%
8	12972	5.1%
5	9891	3.9%
4	6309	2.5%
6	4526	1.8%
9	285	0.1%

Latin

Value	Count	Frequency (%)
e	480000	40.0%
L	240000	20.0%
v	240000	20.0%
l	240000	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1455270	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	480000	33.0%
L	240000	16.5%
v	240000	16.5%
l	240000	16.5%
0	87917	6.0%
3	41784	2.9%
7	38362	2.6%
1	36380	2.5%
2	16844	1.2%
8	12972	0.9%
Other values (4)	21011	1.4%

first_utm_medium_c
Categorical

HIGH CORRELATION

Distinct	45
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.7 MiB

Level0	54338
Level2	27029
Level6	23912
Level3	20009
Level4	18509
Other values (40)	96203

Length

Max length	7
Median length	6
Mean length	6.257395833
Min length	6

Characters and Unicode

Total characters	1501775
Distinct characters	14
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Level0
2nd row	Level1
3rd row	Level2
4th row	Level3
5th row	Level2

Common Values

Value	Count	Frequency (%)
Level0	54338	22.6%
Level2	27029	11.3%
Level6	23912	10.0%
Level3	20009	8.3%
Level4	18509	7.7%
Level9	15595	6.5%
Level11	9628	4.0%
Level5	9097	3.8%
Level8	7381	3.1%
Level20	4187	1.7%
Other values (35)	50315	21.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
level0	54338	22.6%
level2	27029	11.3%
level6	23912	10.0%
level3	20009	8.3%
level4	18509	7.7%
level9	15595	6.5%
level11	9628	4.0%
level5	9097	3.8%
level8	7381	3.1%
level20	4187	1.7%
Other values (35)	50315	21.0%

Most occurring characters

Value	Count	Frequency (%)
e	480000	32.0%
L	240000	16.0%
v	240000	16.0%
l	240000	16.0%
0	66127	4.4%
3	45361	3.0%
2	43948	2.9%
1	42378	2.8%
6	31235	2.1%
4	26575	1.8%
Other values (4)	46151	3.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	960000	63.9%
Decimal Number	301775	20.1%
Uppercase Letter	240000	16.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	66127	21.9%
3	45361	15.0%
2	43948	14.6%
1	42378	14.0%
6	31235	10.4%
4	26575	8.8%
9	19569	6.5%
5	14132	4.7%
8	9223	3.1%
7	3227	1.1%

Lowercase Letter

Value	Count	Frequency (%)
e	480000	50.0%
v	240000	25.0%
l	240000	25.0%

Uppercase Letter

Value	Count	Frequency (%)
L	240000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1200000	79.9%
Common	301775	20.1%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	66127	21.9%
3	45361	15.0%
2	43948	14.6%
1	42378	14.0%
6	31235	10.4%
4	26575	8.8%
9	19569	6.5%
5	14132	4.7%
8	9223	3.1%
7	3227	1.1%

Latin

Value	Count	Frequency (%)
e	480000	40.0%
L	240000	20.0%
v	240000	20.0%
l	240000	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1501775	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	480000	32.0%
L	240000	16.0%
v	240000	16.0%
l	240000	16.0%
0	66127	4.4%
3	45361	3.0%
2	43948	2.9%
1	42378	2.8%
6	31235	2.1%
4	26575	1.8%
Other values (4)	46151	3.1%

first_utm_source_c
Categorical

HIGH CARDINALITY

Distinct	142
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.7 MiB

Level2	83146
Level0	56709
Level7	18719
Level4	16133
Level6	15728
Other values (137)	49565

Length

Max length	8
Median length	6
Mean length	6.1574625
Min length	6

Characters and Unicode

Total characters	1477791
Distinct characters	14
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	33 ?
Unique (%)	< 0.1%

Sample

1st row	Level0
2nd row	Level1
3rd row	Level2
4th row	Level3
5th row	Level2

Common Values

Value	Count	Frequency (%)
Level2	83146	34.6%
Level0	56709	23.6%
Level7	18719	7.8%
Level4	16133	6.7%
Level6	15728	6.6%
Level16	11081	4.6%
Level5	5517	2.3%
Level14	4856	2.0%
Level11	4415	1.8%
Level12	4154	1.7%
Other values (132)	19542	8.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
level2	83146	34.6%
level0	56709	23.6%
level7	18719	7.8%
level4	16133	6.7%
level6	15728	6.6%
level16	11081	4.6%
level5	5517	2.3%
level14	4856	2.0%
level11	4415	1.8%
level12	4154	1.7%
Other values (132)	19542	8.1%

Most occurring characters

Value	Count	Frequency (%)
e	480000	32.5%
L	240000	16.2%
v	240000	16.2%
l	240000	16.2%
2	94419	6.4%
0	57225	3.9%
1	37251	2.5%
6	27517	1.9%
4	21857	1.5%
7	19210	1.3%
Other values (4)	20312	1.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	960000	65.0%
Decimal Number	277791	18.8%
Uppercase Letter	240000	16.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	94419	34.0%
0	57225	20.6%
1	37251	13.4%
6	27517	9.9%
4	21857	7.9%
7	19210	6.9%
5	8368	3.0%
9	4702	1.7%
3	4025	1.4%
8	3217	1.2%

Lowercase Letter

Value	Count	Frequency (%)
e	480000	50.0%
v	240000	25.0%
l	240000	25.0%

Uppercase Letter

Value	Count	Frequency (%)
L	240000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1200000	81.2%
Common	277791	18.8%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	94419	34.0%
0	57225	20.6%
1	37251	13.4%
6	27517	9.9%
4	21857	7.9%
7	19210	6.9%
5	8368	3.0%
9	4702	1.7%
3	4025	1.4%
8	3217	1.2%

Latin

Value	Count	Frequency (%)
e	480000	40.0%
L	240000	20.0%
v	240000	20.0%
l	240000	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1477791	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	480000	32.5%
L	240000	16.2%
v	240000	16.2%
l	240000	16.2%
2	94419	6.4%
0	57225	3.9%
1	37251	2.5%
6	27517	1.9%
4	21857	1.5%
7	19210	1.3%
Other values (4)	20312	1.4%

total_leads_droppped
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	57
Distinct (%)	< 0.1%
Missing	826
Missing (%)	0.3%
Infinite	0
Infinite (%)	0.0%
Mean	1.650810707

Minimum	1
Maximum	89
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	4
Maximum	89
Range	88
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.365227635
Coefficient of variation (CV)	0.8270043496
Kurtosis	406.0823408
Mean	1.650810707
Median Absolute Deviation (MAD)	0
Skewness	12.56359153
Sum	394831
Variance	1.863846495
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	145967	60.8%
2	60640	25.3%
3	19854	8.3%
4	6881	2.9%
5	2817	1.2%
6	1267	0.5%
7	631	0.3%
8	361	0.2%
9	203	0.1%
10	120	0.1%
Other values (47)	433	0.2%
(Missing)	826	0.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	145967	60.8%
2	60640	25.3%
3	19854	8.3%
4	6881	2.9%
5	2817	1.2%
6	1267	0.5%
7	631	0.3%
8	361	0.2%
9	203	0.1%
10	120	0.1%

Value	Count	Frequency (%)
89	2	< 0.1%
71	1	< 0.1%
60	1	< 0.1%
58	1	< 0.1%
54	1	< 0.1%
53	1	< 0.1%
52	2	< 0.1%
51	2	< 0.1%
50	2	< 0.1%
48	2	< 0.1%

referred_lead
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	826
Missing (%)	0.3%
Memory size	3.7 MiB

0.0	231430
1.0	7744

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	717522
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	231430	96.4%
1.0	7744	3.2%
(Missing)	826	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	231430	96.8%
1.0	7744	3.2%

Most occurring characters

Value	Count	Frequency (%)
0	470604	65.6%
.	239174	33.3%
1	7744	1.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	478348	66.7%
Other Punctuation	239174	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	470604	98.4%
1	7744	1.6%

Other Punctuation

Value	Count	Frequency (%)
.	239174	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	717522	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	470604	65.6%
.	239174	33.3%
1	7744	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	717522	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	470604	65.6%
.	239174	33.3%
1	7744	1.1%

1_on_1_industry_mentorship
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

call_us_button_clicked
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	239998
Missing (%)	> 99.9%
Memory size	3.7 MiB

2.0	1
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	6
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	2.0
2nd row	1.0

Common Values

Value	Count	Frequency (%)
2.0	1	< 0.1%
1.0	1	< 0.1%
(Missing)	239998	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	1	50.0%
1.0	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
.	2	33.3%
0	2	33.3%
2	1	16.7%
1	1	16.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4	66.7%
Other Punctuation	2	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2	50.0%
2	1	25.0%
1	1	25.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	6	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	2	33.3%
0	2	33.3%
2	1	16.7%
1	1	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	2	33.3%
0	2	33.3%
2	1	16.7%
1	1	16.7%

career_assistance
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	75.0%
Missing	239996
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	2
2.0	1
3.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	12
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	50.0%

Sample

1st row	2.0
2nd row	3.0
3rd row	1.0
4th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2	< 0.1%
2.0	1	< 0.1%
3.0	1	< 0.1%
(Missing)	239996	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2	50.0%
2.0	1	25.0%
3.0	1	25.0%

Most occurring characters

Value	Count	Frequency (%)
.	4	33.3%
0	4	33.3%
1	2	16.7%
2	1	8.3%
3	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	8	66.7%
Other Punctuation	4	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	50.0%
1	2	25.0%
2	1	12.5%
3	1	12.5%

Other Punctuation

Value	Count	Frequency (%)
.	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	4	33.3%
0	4	33.3%
1	2	16.7%
2	1	8.3%
3	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	4	33.3%
0	4	33.3%
1	2	16.7%
2	1	8.3%
3	1	8.3%

career_coach
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

career_impact
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	60.0%
Missing	239995
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	2
3.0	2
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	15
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	20.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	3.0
4th row	2.0
5th row	3.0

Common Values

Value	Count	Frequency (%)
1.0	2	< 0.1%
3.0	2	< 0.1%
2.0	1	< 0.1%
(Missing)	239995	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2	40.0%
3.0	2	40.0%
2.0	1	20.0%

Most occurring characters

Value	Count	Frequency (%)
.	5	33.3%
0	5	33.3%
1	2	13.3%
3	2	13.3%
2	1	6.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	66.7%
Other Punctuation	5	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	50.0%
1	2	20.0%
3	2	20.0%
2	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	5	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	15	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	5	33.3%
0	5	33.3%
1	2	13.3%
3	2	13.3%
2	1	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	15	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	5	33.3%
0	5	33.3%
1	2	13.3%
3	2	13.3%
2	1	6.7%

careers
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	8
Distinct (%)	40.0%
Missing	239980
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	4

Minimum	1
Maximum	29
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3.25
95-th percentile	11.9
Maximum	29
Range	28
Interquartile range (IQR)	2.25

Descriptive statistics

Standard deviation	6.496962853
Coefficient of variation (CV)	1.624240713
Kurtosis	12.45407757
Mean	4
Median Absolute Deviation (MAD)	1
Skewness	3.371355954
Sum	80
Variance	42.21052632
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
1	9	< 0.1%
2	5	< 0.1%
3	1	< 0.1%
29	1	< 0.1%
9	1	< 0.1%
11	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
(Missing)	239980	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	9	< 0.1%
2	5	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
9	1	< 0.1%
11	1	< 0.1%
29	1	< 0.1%

Value	Count	Frequency (%)
29	1	< 0.1%
11	1	< 0.1%
9	1	< 0.1%
5	1	< 0.1%
4	1	< 0.1%
3	1	< 0.1%
2	5	< 0.1%
1	9	< 0.1%

chat_clicked
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

companies
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	239998
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	1
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	6
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	1.0
2nd row	2.0

Common Values

Value	Count	Frequency (%)
1.0	1	< 0.1%
2.0	1	< 0.1%
(Missing)	239998	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	1	50.0%
2.0	1	50.0%

Most occurring characters

Value	Count	Frequency (%)
.	2	33.3%
0	2	33.3%
1	1	16.7%
2	1	16.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4	66.7%
Other Punctuation	2	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2	50.0%
1	1	25.0%
2	1	25.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	6	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	2	33.3%
0	2	33.3%
1	1	16.7%
2	1	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	2	33.3%
0	2	33.3%
1	1	16.7%
2	1	16.7%

download_button_clicked
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	31
Distinct (%)	29.0%
Missing	239893
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	10.55140187

Minimum	1
Maximum	98
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	3
Q3	7.5
95-th percentile	46.8
Maximum	98
Range	97
Interquartile range (IQR)	6.5

Descriptive statistics

Standard deviation	18.65588766
Coefficient of variation (CV)	1.768095641
Kurtosis	9.051424841
Mean	10.55140187
Median Absolute Deviation (MAD)	2
Skewness	2.873550338
Sum	1129
Variance	348.0421442
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
1	31	< 0.1%
2	22	< 0.1%
3	10	< 0.1%
4	8	< 0.1%
7	3	< 0.1%
5	3	< 0.1%
6	3	< 0.1%
8	2	< 0.1%
36	2	< 0.1%
57	2	< 0.1%
Other values (21)	21	< 0.1%
(Missing)	239893	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	31	< 0.1%
2	22	< 0.1%
3	10	< 0.1%
4	8	< 0.1%
5	3	< 0.1%
6	3	< 0.1%
7	3	< 0.1%
8	2	< 0.1%
9	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
98	1	< 0.1%
97	1	< 0.1%
75	1	< 0.1%
57	2	< 0.1%
48	1	< 0.1%
44	1	< 0.1%
40	1	< 0.1%
36	2	< 0.1%
34	1	< 0.1%
33	1	< 0.1%

download_syllabus
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

emi_partner_click
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	39
Distinct (%)	49.4%
Missing	239921
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	27.86075949

Minimum	1
Maximum	319
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1.9
Q1	4
median	9
Q3	27
95-th percentile	122.1
Maximum	319
Range	318
Interquartile range (IQR)	23

Descriptive statistics

Standard deviation	48.4981454
Coefficient of variation (CV)	1.74073307
Kurtosis	16.75134965
Mean	27.86075949
Median Absolute Deviation (MAD)	7
Skewness	3.58802169
Sum	2201
Variance	2352.070107
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=39)

Value	Count	Frequency (%)
2	9	< 0.1%
6	7	< 0.1%
5	5	< 0.1%
4	5	< 0.1%
11	5	< 0.1%
8	4	< 0.1%
1	4	< 0.1%
3	3	< 0.1%
13	3	< 0.1%
17	2	< 0.1%
Other values (29)	32	< 0.1%
(Missing)	239921	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	4	< 0.1%
2	9	< 0.1%
3	3	< 0.1%
4	5	< 0.1%
5	5	< 0.1%
6	7	< 0.1%
7	2	< 0.1%
8	4	< 0.1%
9	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
319	1	< 0.1%
164	1	< 0.1%
133	1	< 0.1%
123	1	< 0.1%
122	1	< 0.1%
108	1	< 0.1%
104	1	< 0.1%
97	1	< 0.1%
83	1	< 0.1%
74	1	< 0.1%

emi_plans_clicked
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	34
Distinct (%)	55.7%
Missing	239939
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	42.72131148

Minimum	1
Maximum	246
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	10
Q3	66
95-th percentile	204
Maximum	246
Range	245
Interquartile range (IQR)	64

Descriptive statistics

Standard deviation	63.34880455
Coefficient of variation (CV)	1.48283848
Kurtosis	3.218107336
Mean	42.72131148
Median Absolute Deviation (MAD)	9
Skewness	1.934837832
Sum	2606
Variance	4013.071038
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
1	11	< 0.1%
2	7	< 0.1%
3	4	< 0.1%
5	4	< 0.1%
52	2	< 0.1%
66	2	< 0.1%
25	2	< 0.1%
21	2	< 0.1%
10	2	< 0.1%
71	1	< 0.1%
Other values (24)	24	< 0.1%
(Missing)	239939	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	11	< 0.1%
2	7	< 0.1%
3	4	< 0.1%
4	1	< 0.1%
5	4	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
10	2	< 0.1%
11	1	< 0.1%
15	1	< 0.1%

Value	Count	Frequency (%)
246	1	< 0.1%
240	1	< 0.1%
232	1	< 0.1%
204	1	< 0.1%
152	1	< 0.1%
133	1	< 0.1%
124	1	< 0.1%
110	1	< 0.1%
107	1	< 0.1%
100	1	< 0.1%

fee_component_click
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	60.0%
Missing	239995
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	3
10.0	1
2.0	1

Length

Max length	4
Median length	3
Mean length	3.2
Min length	3

Characters and Unicode

Total characters	16
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	40.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	10.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	3	< 0.1%
10.0	1	< 0.1%
2.0	1	< 0.1%
(Missing)	239995	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	3	60.0%
10.0	1	20.0%
2.0	1	20.0%

Most occurring characters

Value	Count	Frequency (%)
0	6	37.5%
.	5	31.2%
1	4	25.0%
2	1	6.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	11	68.8%
Other Punctuation	5	31.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	6	54.5%
1	4	36.4%
2	1	9.1%

Other Punctuation

Value	Count	Frequency (%)
.	5	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	16	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	6	37.5%
.	5	31.2%
1	4	25.0%
2	1	6.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	16	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	6	37.5%
.	5	31.2%
1	4	25.0%
2	1	6.2%

hiring_partners
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	22.2%
Missing	239991
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	5
2.0	4

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	27
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2.0
2nd row	1.0
3rd row	1.0
4th row	2.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	5	< 0.1%
2.0	4	< 0.1%
(Missing)	239991	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5	55.6%
2.0	4	44.4%

Most occurring characters

Value	Count	Frequency (%)
.	9	33.3%
0	9	33.3%
1	5	18.5%
2	4	14.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	18	66.7%
Other Punctuation	9	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	9	50.0%
1	5	27.8%
2	4	22.2%

Other Punctuation

Value	Count	Frequency (%)
.	9	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	27	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	9	33.3%
0	9	33.3%
1	5	18.5%
2	4	14.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	27	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	9	33.3%
0	9	33.3%
1	5	18.5%
2	4	14.8%

homepage_upgrad_support_number_clicked
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

industry_projects_case_studies
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

live_chat_button_clicked
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	22.2%
Missing	239982
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	10
2.0	3
3.0	3
4.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	54
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	2.0
3rd row	4.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	10	< 0.1%
2.0	3	< 0.1%
3.0	3	< 0.1%
4.0	2	< 0.1%
(Missing)	239982	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	10	55.6%
2.0	3	16.7%
3.0	3	16.7%
4.0	2	11.1%

Most occurring characters

Value	Count	Frequency (%)
.	18	33.3%
0	18	33.3%
1	10	18.5%
2	3	5.6%
3	3	5.6%
4	2	3.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	36	66.7%
Other Punctuation	18	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	18	50.0%
1	10	27.8%
2	3	8.3%
3	3	8.3%
4	2	5.6%

Other Punctuation

Value	Count	Frequency (%)
.	18	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	54	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	18	33.3%
0	18	33.3%
1	10	18.5%
2	3	5.6%
3	3	5.6%
4	2	3.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	18	33.3%
0	18	33.3%
1	10	18.5%
2	3	5.6%
3	3	5.6%
4	2	3.7%

payment_amount_toggle_mover
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

placement_support
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	66.7%
Missing	239997
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	2
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	9
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	33.3%

Sample

1st row	1.0
2nd row	2.0
3rd row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2	< 0.1%
2.0	1	< 0.1%
(Missing)	239997	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2	66.7%
2.0	1	33.3%

Most occurring characters

Value	Count	Frequency (%)
.	3	33.3%
0	3	33.3%
1	2	22.2%
2	1	11.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6	66.7%
Other Punctuation	3	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3	50.0%
1	2	33.3%
2	1	16.7%

Other Punctuation

Value	Count	Frequency (%)
.	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	9	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	3	33.3%
0	3	33.3%
1	2	22.2%
2	1	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	3	33.3%
0	3	33.3%
1	2	22.2%
2	1	11.1%

placement_support_banner_tab_clicked
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	100.0%
Missing	239999
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	3
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	1.0

Common Values

Value	Count	Frequency (%)
1.0	1	< 0.1%
(Missing)	239999	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2	66.7%
Other Punctuation	1	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1	50.0%
0	1	50.0%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	3	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

program_structure
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	240000
Missing (%)	100.0%
Memory size	3.7 MiB

programme_curriculum
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	100.0%
Missing	239999
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	3
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	1.0

Common Values

Value	Count	Frequency (%)
1.0	1	< 0.1%
(Missing)	239999	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2	66.7%
Other Punctuation	1	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1	50.0%
0	1	50.0%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	3	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

programme_faculty
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	100.0%
Missing	239999
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	3
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	100.0%

Sample

1st row	1.0

Common Values

Value	Count	Frequency (%)
1.0	1	< 0.1%
(Missing)	239999	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	1	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2	66.7%
Other Punctuation	1	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1	50.0%
0	1	50.0%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	3	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1	33.3%
.	1	33.3%
0	1	33.3%

request_callback_on_instant_customer_support_cta_clicked
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	50.0%
Missing	239998
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	6
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2	< 0.1%
(Missing)	239998	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	2	33.3%
.	2	33.3%
0	2	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4	66.7%
Other Punctuation	2	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	2	50.0%
0	2	50.0%

Other Punctuation

Value	Count	Frequency (%)
.	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	6	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	2	33.3%
.	2	33.3%
0	2	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	2	33.3%
.	2	33.3%
0	2	33.3%

shorts_entry_click
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	30.8%
Missing	239987
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	10
32.0	1
9.0	1
4.0	1

Length

Max length	4
Median length	3
Mean length	3.076923077
Min length	3

Characters and Unicode

Total characters	40
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	23.1%

Sample

1st row	32.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	10	< 0.1%
32.0	1	< 0.1%
9.0	1	< 0.1%
4.0	1	< 0.1%
(Missing)	239987	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	10	76.9%
32.0	1	7.7%
9.0	1	7.7%
4.0	1	7.7%

Most occurring characters

Value	Count	Frequency (%)
.	13	32.5%
0	13	32.5%
1	10	25.0%
3	1	2.5%
2	1	2.5%
9	1	2.5%
4	1	2.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	27	67.5%
Other Punctuation	13	32.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	13	48.1%
1	10	37.0%
3	1	3.7%
2	1	3.7%
9	1	3.7%
4	1	3.7%

Other Punctuation

Value	Count	Frequency (%)
.	13	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	40	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	13	32.5%
0	13	32.5%
1	10	25.0%
3	1	2.5%
2	1	2.5%
9	1	2.5%
4	1	2.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	40	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	13	32.5%
0	13	32.5%
1	10	25.0%
3	1	2.5%
2	1	2.5%
9	1	2.5%
4	1	2.5%

social_referral_click
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	4
Distinct (%)	80.0%
Missing	239995
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	2
3.0	1
2.0	1
8.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	15
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	60.0%

Sample

1st row	3.0
2nd row	2.0
3rd row	1.0
4th row	8.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2	< 0.1%
3.0	1	< 0.1%
2.0	1	< 0.1%
8.0	1	< 0.1%
(Missing)	239995	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2	40.0%
3.0	1	20.0%
2.0	1	20.0%
8.0	1	20.0%

Most occurring characters

Value	Count	Frequency (%)
.	5	33.3%
0	5	33.3%
1	2	13.3%
3	1	6.7%
2	1	6.7%
8	1	6.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10	66.7%
Other Punctuation	5	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	5	50.0%
1	2	20.0%
3	1	10.0%
2	1	10.0%
8	1	10.0%

Other Punctuation

Value	Count	Frequency (%)
.	5	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	15	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	5	33.3%
0	5	33.3%
1	2	13.3%
3	1	6.7%
2	1	6.7%
8	1	6.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	15	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	5	33.3%
0	5	33.3%
1	2	13.3%
3	1	6.7%
2	1	6.7%
8	1	6.7%

specialisation_tab_clicked
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	31
Distinct (%)	70.5%
Missing	239956
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	36.29545455

Minimum	1
Maximum	196
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	4.75
median	12
Q3	58.75
95-th percentile	110.95
Maximum	196
Range	195
Interquartile range (IQR)	54

Descriptive statistics

Standard deviation	45.44742915
Coefficient of variation (CV)	1.252152087
Kurtosis	2.69263448
Mean	36.29545455
Median Absolute Deviation (MAD)	11
Skewness	1.666444767
Sum	1597
Variance	2065.468816
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
1	5	< 0.1%
8	3	< 0.1%
9	3	< 0.1%
4	3	< 0.1%
13	2	< 0.1%
6	2	< 0.1%
2	2	< 0.1%
88	1	< 0.1%
11	1	< 0.1%
98	1	< 0.1%
Other values (21)	21	< 0.1%
(Missing)	239956	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	5	< 0.1%
2	2	< 0.1%
3	1	< 0.1%
4	3	< 0.1%
5	1	< 0.1%
6	2	< 0.1%
7	1	< 0.1%
8	3	< 0.1%
9	3	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
196	1	< 0.1%
150	1	< 0.1%
112	1	< 0.1%
105	1	< 0.1%
102	1	< 0.1%
98	1	< 0.1%
88	1	< 0.1%
80	1	< 0.1%
75	1	< 0.1%
65	1	< 0.1%

specializations
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	3
Distinct (%)	75.0%
Missing	239996
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	2
3.0	1
2.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	12
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	50.0%

Sample

1st row	1.0
2nd row	3.0
3rd row	2.0
4th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	2	< 0.1%
3.0	1	< 0.1%
2.0	1	< 0.1%
(Missing)	239996	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	2	50.0%
3.0	1	25.0%
2.0	1	25.0%

Most occurring characters

Value	Count	Frequency (%)
.	4	33.3%
0	4	33.3%
1	2	16.7%
3	1	8.3%
2	1	8.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	8	66.7%
Other Punctuation	4	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4	50.0%
1	2	25.0%
3	1	12.5%
2	1	12.5%

Other Punctuation

Value	Count	Frequency (%)
.	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	12	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	4	33.3%
0	4	33.3%
1	2	16.7%
3	1	8.3%
2	1	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	12	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	4	33.3%
0	4	33.3%
1	2	16.7%
3	1	8.3%
2	1	8.3%

specilization_click
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	85.7%
Missing	239993
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	5.285714286

Minimum	1
Maximum	13
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1.5
median	5
Q3	7.5
95-th percentile	11.8
Maximum	13
Range	12
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.498677054
Coefficient of variation (CV)	0.8511010643
Kurtosis	-0.2462217301
Mean	5.285714286
Median Absolute Deviation (MAD)	4
Skewness	0.8143570582
Sum	37
Variance	20.23809524
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	2	< 0.1%
6	1	< 0.1%
5	1	< 0.1%
2	1	< 0.1%
9	1	< 0.1%
13	1	< 0.1%
(Missing)	239993	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	2	< 0.1%
2	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
9	1	< 0.1%
13	1	< 0.1%

Value	Count	Frequency (%)
13	1	< 0.1%
9	1	< 0.1%
6	1	< 0.1%
5	1	< 0.1%
2	1	< 0.1%
1	2	< 0.1%

syllabus
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	10
Distinct (%)	34.5%
Missing	239971
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	7.068965517

Minimum	1
Maximum	50
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	4
95-th percentile	37
Maximum	50
Range	49
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	12.45257011
Coefficient of variation (CV)	1.761583089
Kurtosis	5.839513432
Mean	7.068965517
Median Absolute Deviation (MAD)	1
Skewness	2.562720807
Sum	205
Variance	155.0665025
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	10	< 0.1%
2	7	< 0.1%
4	4	< 0.1%
3	2	< 0.1%
34	1	< 0.1%
17	1	< 0.1%
6	1	< 0.1%
13	1	< 0.1%
50	1	< 0.1%
39	1	< 0.1%
(Missing)	239971	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	10	< 0.1%
2	7	< 0.1%
3	2	< 0.1%
4	4	< 0.1%
6	1	< 0.1%
13	1	< 0.1%
17	1	< 0.1%
34	1	< 0.1%
39	1	< 0.1%
50	1	< 0.1%

Value	Count	Frequency (%)
50	1	< 0.1%
39	1	< 0.1%
34	1	< 0.1%
17	1	< 0.1%
13	1	< 0.1%
6	1	< 0.1%
4	4	< 0.1%
3	2	< 0.1%
2	7	< 0.1%
1	10	< 0.1%

syllabus_expand
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	49
Distinct (%)	52.1%
Missing	239906
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	83.44680851

Minimum	1
Maximum	930
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	6
Q3	71.5
95-th percentile	390.85
Maximum	930
Range	929
Interquartile range (IQR)	69.5

Descriptive statistics

Standard deviation	188.4179532
Coefficient of variation (CV)	2.257940796
Kurtosis	11.97359139
Mean	83.44680851
Median Absolute Deviation (MAD)	5
Skewness	3.420265609
Sum	7844
Variance	35501.3251
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=49)

Value	Count	Frequency (%)
2	15	< 0.1%
1	11	< 0.1%
4	7	< 0.1%
3	6	< 0.1%
6	5	< 0.1%
5	4	< 0.1%
8	3	< 0.1%
11	2	< 0.1%
42	1	< 0.1%
72	1	< 0.1%
Other values (39)	39	< 0.1%
(Missing)	239906	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	11	< 0.1%
2	15	< 0.1%
3	6	< 0.1%
4	7	< 0.1%
5	4	< 0.1%
6	5	< 0.1%
7	1	< 0.1%
8	3	< 0.1%
10	1	< 0.1%
11	2	< 0.1%

Value	Count	Frequency (%)
930	1	< 0.1%
928	1	< 0.1%
887	1	< 0.1%
739	1	< 0.1%
450	1	< 0.1%
359	1	< 0.1%
309	1	< 0.1%
275	1	< 0.1%
254	1	< 0.1%
242	1	< 0.1%

syllabus_submodule_expand
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	21
Distinct (%)	50.0%
Missing	239958
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	39.71428571

Minimum	1
Maximum	457
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1.25
median	5
Q3	21
95-th percentile	179.5
Maximum	457
Range	456
Interquartile range (IQR)	19.75

Descriptive statistics

Standard deviation	92.79173789
Coefficient of variation (CV)	2.336482609
Kurtosis	12.41907508
Mean	39.71428571
Median Absolute Deviation (MAD)	4
Skewness	3.458610702
Sum	1668
Variance	8610.30662
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
1	11	< 0.1%
5	4	< 0.1%
2	3	< 0.1%
3	3	< 0.1%
14	2	< 0.1%
21	2	< 0.1%
4	2	< 0.1%
8	2	< 0.1%
9	1	< 0.1%
56	1	< 0.1%
Other values (11)	11	< 0.1%
(Missing)	239958	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	11	< 0.1%
2	3	< 0.1%
3	3	< 0.1%
4	2	< 0.1%
5	4	< 0.1%
7	1	< 0.1%
8	2	< 0.1%
9	1	< 0.1%
14	2	< 0.1%
20	1	< 0.1%

Value	Count	Frequency (%)
457	1	< 0.1%
357	1	< 0.1%
181	1	< 0.1%
151	1	< 0.1%
118	1	< 0.1%
60	1	< 0.1%
56	1	< 0.1%
52	1	< 0.1%
38	1	< 0.1%
22	1	< 0.1%

tab_career_assistance
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	9
Distinct (%)	36.0%
Missing	239975
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	7.84

Minimum	1
Maximum	57
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	2
Q3	7
95-th percentile	26.4
Maximum	57
Range	56
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	12.85392288
Coefficient of variation (CV)	1.639530979
Kurtosis	8.616928893
Mean	7.84
Median Absolute Deviation (MAD)	1
Skewness	2.783657263
Sum	196
Variance	165.2233333
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
2	9	< 0.1%
1	6	< 0.1%
4	3	< 0.1%
24	2	< 0.1%
57	1	< 0.1%
8	1	< 0.1%
7	1	< 0.1%
13	1	< 0.1%
27	1	< 0.1%
(Missing)	239975	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	6	< 0.1%
2	9	< 0.1%
4	3	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
13	1	< 0.1%
24	2	< 0.1%
27	1	< 0.1%
57	1	< 0.1%

Value	Count	Frequency (%)
57	1	< 0.1%
27	1	< 0.1%
24	2	< 0.1%
13	1	< 0.1%
8	1	< 0.1%
7	1	< 0.1%
4	3	< 0.1%
2	9	< 0.1%
1	6	< 0.1%

tab_job_opportunities
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	9
Distinct (%)	47.4%
Missing	239981
Missing (%)	> 99.9%
Infinite	0
Infinite (%)	0.0%
Mean	4.578947368

Minimum	1
Maximum	14
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.7 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	8
95-th percentile	12.2
Maximum	14
Range	13
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	4.694154633
Coefficient of variation (CV)	1.025160207
Kurtosis	-0.7022014451
Mean	4.578947368
Median Absolute Deviation (MAD)	1
Skewness	0.9955343554
Sum	87
Variance	22.03508772
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
1	8	< 0.1%
2	3	< 0.1%
12	2	< 0.1%
14	1	< 0.1%
3	1	< 0.1%
11	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
10	1	< 0.1%
(Missing)	239981	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	8	< 0.1%
2	3	< 0.1%
3	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%
12	2	< 0.1%
14	1	< 0.1%

Value	Count	Frequency (%)
14	1	< 0.1%
12	2	< 0.1%
11	1	< 0.1%
10	1	< 0.1%
6	1	< 0.1%
5	1	< 0.1%
3	1	< 0.1%
2	3	< 0.1%
1	8	< 0.1%

tab_student_support
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	62.5%
Missing	239992
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	3
2.0	2
6.0	1
3.0	1
8.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	24
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	37.5%

Sample

1st row	1.0
2nd row	6.0
3rd row	1.0
4th row	2.0
5th row	3.0

Common Values

Value	Count	Frequency (%)
1.0	3	< 0.1%
2.0	2	< 0.1%
6.0	1	< 0.1%
3.0	1	< 0.1%
8.0	1	< 0.1%
(Missing)	239992	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	3	37.5%
2.0	2	25.0%
6.0	1	12.5%
3.0	1	12.5%
8.0	1	12.5%

Most occurring characters

Value	Count	Frequency (%)
.	8	33.3%
0	8	33.3%
1	3	12.5%
2	2	8.3%
6	1	4.2%
3	1	4.2%
8	1	4.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	16	66.7%
Other Punctuation	8	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	8	50.0%
1	3	18.8%
2	2	12.5%
6	1	6.2%
3	1	6.2%
8	1	6.2%

Other Punctuation

Value	Count	Frequency (%)
.	8	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	8	33.3%
0	8	33.3%
1	3	12.5%
2	2	8.3%
6	1	4.2%
3	1	4.2%
8	1	4.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	8	33.3%
0	8	33.3%
1	3	12.5%
2	2	8.3%
6	1	4.2%
3	1	4.2%
8	1	4.2%

view_programs_page
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	41.7%
Missing	239988
Missing (%)	> 99.9%
Memory size	3.7 MiB

2.0	4
3.0	3
1.0	3
4.0	1
11.0	1

Length

Max length	4
Median length	3
Mean length	3.083333333
Min length	3

Characters and Unicode

Total characters	37
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	16.7%

Sample

1st row	4.0
2nd row	3.0
3rd row	1.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	4	< 0.1%
3.0	3	< 0.1%
1.0	3	< 0.1%
4.0	1	< 0.1%
11.0	1	< 0.1%
(Missing)	239988	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2.0	4	33.3%
3.0	3	25.0%
1.0	3	25.0%
4.0	1	8.3%
11.0	1	8.3%

Most occurring characters

Value	Count	Frequency (%)
.	12	32.4%
0	12	32.4%
1	5	13.5%
2	4	10.8%
3	3	8.1%
4	1	2.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	25	67.6%
Other Punctuation	12	32.4%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	12	48.0%
1	5	20.0%
2	4	16.0%
3	3	12.0%
4	1	4.0%

Other Punctuation

Value	Count	Frequency (%)
.	12	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	37	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	12	32.4%
0	12	32.4%
1	5	13.5%
2	4	10.8%
3	3	8.1%
4	1	2.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	37	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	12	32.4%
0	12	32.4%
1	5	13.5%
2	4	10.8%
3	3	8.1%
4	1	2.7%

whatsapp_chat_click
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	20.0%
Missing	239975
Missing (%)	> 99.9%
Memory size	3.7 MiB

1.0	15
2.0	5
3.0	3
16.0	1
13.0	1

Length

Max length	4
Median length	3
Mean length	3.08
Min length	3

Characters and Unicode

Total characters	77
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	8.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	15	< 0.1%
2.0	5	< 0.1%
3.0	3	< 0.1%
16.0	1	< 0.1%
13.0	1	< 0.1%
(Missing)	239975	> 99.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	15	60.0%
2.0	5	20.0%
3.0	3	12.0%
16.0	1	4.0%
13.0	1	4.0%

Most occurring characters

Value	Count	Frequency (%)
.	25	32.5%
0	25	32.5%
1	17	22.1%
2	5	6.5%
3	4	5.2%
6	1	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	52	67.5%
Other Punctuation	25	32.5%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	25	48.1%
1	17	32.7%
2	5	9.6%
3	4	7.7%
6	1	1.9%

Other Punctuation

Value	Count	Frequency (%)
.	25	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	77	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	25	32.5%
0	25	32.5%
1	17	22.1%
2	5	6.5%
3	4	5.2%
6	1	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	77	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	25	32.5%
0	25	32.5%
1	17	22.1%
2	5	6.5%
3	4	5.2%
6	1	1.3%

app_complete_flag
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.7 MiB

0	120000
1	120000

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	240000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	120000	50.0%
1	120000	50.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	120000	50.0%
1	120000	50.0%

Most occurring characters

Value	Count	Frequency (%)
0	120000	50.0%
1	120000	50.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	240000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	120000	50.0%
1	120000	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	240000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	120000	50.0%
1	120000	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	240000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	120000	50.0%
1	120000	50.0%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	created_date	city_mapped	first_platform_c	first_utm_medium_c	first_utm_source_c	total_leads_droppped	1_on_1_industry_mentorship	call_us_button_clicked	career_assistance	career_coach	career_impact	careers	chat_clicked	companies	download_button_clicked	download_syllabus	emi_partner_click	emi_plans_clicked	fee_component_click	hiring_partners	homepage_upgrad_support_number_clicked	industry_projects_case_studies	live_chat_button_clicked	payment_amount_toggle_mover	placement_support	placement_support_banner_tab_clicked	program_structure	programme_curriculum	programme_faculty	request_callback_on_instant_customer_support_cta_clicked	shorts_entry_click	social_referral_click	specialisation_tab_clicked	specializations	specilization_click	syllabus	syllabus_expand	syllabus_submodule_expand	tab_career_assistance	tab_job_opportunities	tab_student_support	view_programs_page	whatsapp_chat_click
0	2021-08-13 10:44:09	mumbai	Level0	Level0	Level0	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	2021-11-04 06:34:10	ncr	Level1	Level1	Level1	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	2021-07-29 14:01:00	meerut	Level0	Level2	Level2	2.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	2021-12-01 13:21:54	ncr	Level1	Level3	Level3	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	2021-12-10 07:22:51	ahmedabad	Level2	Level2	Level2	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
5	2022-01-19 11:46:52	mumbai	Level0	Level0	Level0	2.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
6	2021-08-03 05:21:45	imphal	Level3	Level0	Level0	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
7	2021-08-20 10:01:54	kanpur	Level0	Level4	Level2	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
8	2021-08-23 05:54:58	hyderabad	Level0	Level4	Level2	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
9	2021-08-18 15:33:52	himachal pradesh	Level1	Level5	Level4	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Last rows

	created_date	city_mapped	first_platform_c	first_utm_medium_c	first_utm_source_c	total_leads_droppped	1_on_1_industry_mentorship	call_us_button_clicked	career_assistance	career_coach	career_impact	careers	chat_clicked	companies	download_button_clicked	download_syllabus	emi_partner_click	emi_plans_clicked	fee_component_click	hiring_partners	homepage_upgrad_support_number_clicked	industry_projects_case_studies	live_chat_button_clicked	payment_amount_toggle_mover	placement_support	placement_support_banner_tab_clicked	program_structure	programme_curriculum	programme_faculty	request_callback_on_instant_customer_support_cta_clicked	shorts_entry_click	social_referral_click	specialisation_tab_clicked	specializations	specilization_click	syllabus	syllabus_expand	syllabus_submodule_expand	tab_career_assistance	tab_job_opportunities	tab_student_support	view_programs_page	whatsapp_chat_click	app_complete_flag
239990	2021-12-24 10:26:15	pune	Level0	Level6	Level7	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239991	2021-11-27 05:43:52	mangalore	Level0	Level8	Level2	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239992	2021-08-06 16:54:08	bhopal	Level3	Level0	Level0	5.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239993	2021-08-03 14:36:03	cairo	Level0	Level6	Level7	3.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239994	2022-01-02 14:01:03	ncr	Level0	Level9	Level2	2.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239995	2021-08-12 10:41:15	kolkata	Level0	Level9	Level2	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239996	2021-11-29 06:16:01	deesa	Level3	Level33	Level16	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239997	2021-08-07 07:27:07	hyderabad	Level3	Level3	Level23	1.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239998	2022-01-24 07:44:32	pune	Level8	Level20	Level14	3.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1
239999	2021-12-23 17:49:16	surat	Level0	Level12	Level9	2.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	1

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Space Separator

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters